Supercomputer Makes a Scientific Discovery

Computer programs seem to be replacing every profession these days: writers, artists, psychologists, police officers, the list goes on and on. Today, researchers claimed that we can add scientists to that list, as a computer program has single-handedly made a scientific discovery.

The program, named KnIT, has the ability to read 100,000 papers in two hours, more than a human scientist could hope to read in his or her lifetime. Or, more accurately, rather than "reading," the program scans for information about a specific topic. In this case, the computer scanned for information about the protein p53, which has been shown to suppress tumors in humans. The researchers, and therefore KnIT, were particularly interested in the protein's kinases, or enzymes with which it interacts, as discovering new kinases could yield new methods for cancer treatment.

KnIT was able to correctly identify seven of the nine kinases that were discovered in the past ten years just by scanning papers published up to 2003. Even more impressively, it discovered two kinases that were completely unknown to researchers, just from drawing connections from information that was already available to the scientific community. Early testing has confirmed the veracity of this discovery, although follow-up testing will be necessary to confirm the findings.

Scientists' jobs are still safe, as KnIT is only able to analyze information that human scientists collect, not to mention that KnIT's actual analysis is conducted under the direction of humans. But its creators are hoping that it will solve a major flaw that is widespread in the scientific field: that much more emphasis is placed on gathering new data than thoroughly analyzing the data we already have. "This leads to deep inefficiencies in translating research into progress for humanity," they wrote in a paper that will be presented later this week.

"In general, new p53 kinases are discovered at a rate of one per year," says Olivier Lichtarge, who conducted research for KnIT at Baylor School of Medicine. "We hope to greatly accelerate that rate of discovery."

Not only does this particular program have a great deal of potential within cancer research, but the research team is hoping to extend its data mining applications to other sciences. However, this will not necessarily be a simple endeavor: "We could run into big problems when we try and generalise to more proteins and genes," Lichtarge said. Furthermore, fields such as physics and mathematics tend to document discoveries with equations and graphs rather than words, which would create logistical problems for the scanning process. But the most groundbreaking aspect of this technology may be its ability to introduce the scientific community to the concept of data mining and making new connections from old data as equally valuable to gathering new data.